6048 results for "canc*"

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• Genome and transcriptome sequence data from a myxoid liposarcoma patient

  Genome and transcriptome sequence data from a myxoid liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002620

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002623

• Genome and transcriptome sequence data from a Ewing sarcoma patient

  Genome and transcriptome sequence data from a Ewing sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002625

• Impact of mutational profiles on response of primary oestrogen receptor-positive breast cancers to oestrogen deprivation

  Presurgical studies allow study of the relationship between mutations and response of estrogen receptor positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in Phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 Controls). In poor responders (based on Ki67 change) we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores   occur in approximately 30% of tumours. In Phase II we combine targeted sequencing on another 28 treated patients with Phase I. We find six genes frequently mutated: PIK3CA, TP53, CDH1, MLL3, ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy.

  Dataset EGAD00001002651

• Whole genome sequencing of 98 tumour-normal pairs for the pancreatic neuroendocrine cancer project

  Whole genome sequencing of 98 tumour-normal pairs for the PAEN-AU pancreatic neuroendocrine cancer project.

  Dataset EGAD00001002684

• Breast cancer PDTX sequencing data from Bruna et al, Cell 2016

  Breast cancer PDTX sequencing data from Bruna et al, Cell 2016 - Exome Sequencing - Shallow Whole Genome Sequencing - RRBS Methylation Sequencing

  Dataset EGAD00001002685

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002696

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002697

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002698

• Cancer initiation organoids BAM files

  This dataset contains whole-genome sequencing data files from colon organoid cultures, which were mutated using CRISPR-Cas9 for specific genes (APC, KRAS, TP53 and SMAD4) to generate in vitro transformed cancer cells. After introducing each mutation, the resulting cultures were subjected to whole-genome sequencing. In addition, some cultures were xenotransplanted in recipient mice. The resulting primary tumors and corresponding metastases were subjected to whole-genome sequencing.

  Dataset EGAD00001002719

• Blood dataset - Case

  blood-based gene expression from breast cancer cases

  Dataset EGAD00010001063

• Tumor dataset - Case

  tumor-based gene expression from breast cancer cases

  Dataset EGAD00010001064

• Blood dataset - Case-control

  blood-based gene expression from breast cancer cases and age-matched controls

  Dataset EGAD00010001062

• September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002724

• Whole exome sequencing of bulk primary tumor (and one lymph node metastasis) and matched blood of six non-metastatic breast cancer patients

  Dataset EGAD00001002746

• Single Cell Transcriptomic Analysis of Cellular Heterogeneity in Human Colorectal Tumours

  1,591 single cells from 11 colorectal cancer patients were profiled using Fluidigm based single cell RNA-seq protocol to characterized cellular heterogeneity of colorectal cancer. 630 single cells from 7 cell lines were profiled similarly to benchmark de novo cell type identification algorithms.

  Dataset EGAD00001002727

• Premalignant SOX2 in ovarian cancer patients

  Whole Genome Sequencing data set for the study "Premalignant SOX2 in ovarian cancer patients"

  Dataset EGAD00001002734

• Breast cancer SNP6 arrays_more

  Affymetrix SNP6.0 array breast cancer data

  Dataset EGAD00010001079

• MED12L Gene Alterations Define Aggressive BRCA2-Mutant Prostate Cancers

  Aligned sequence data from 14 Prostate cancer samples with BRCA2 mutations

  Dataset EGAD00001002739

• A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing.

  Dataset EGAD00001002740

• Whole genome sequencing of 63 single cells isolated from bone marrow aspirates of six non-metastatic breast cancer patients after staining for disseminated tumor cells.

  Dataset EGAD00001002745

• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  Whole-exome sequencing (WES) of 216 breast cancer metastasis-normal pairs from patients who underwent a biopsy in the context of the SAFIR01, SAFIR02, SHIVA or MOSCATO prospective trials (France).

  Dataset EGAD00001002747

• Bam files from whole exome sequencing (WES)from multiple laser microdissected regions from tumor and paired biopsies from metastatic lesions.

  In this study we characterized genomic alterations in three bladder cancer patients with metastatic disease courses. Multiple regions were procured by laser microdissection or punctures from primary tumor, lymph node metastases and from distant metastases. Data provided here consist of 35 Bam files for WES (32 Tumors and 2 blood, 1 adjacent normal)

  Dataset EGAD00001002772

• Illumina_RNA_T-XEN_Validation_Cohort

  RNAseq on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer sample of a validation cohort of 60 PDX

  Dataset EGAD00001002883

• Illumina_RNA_MET-CELL_Passages

  RNAseq on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample at early/late passages

  Dataset EGAD00001002884

• CPC-GENE Prostate Cancer Heterogeneity Study

  Raw sequence data, fastq format

  Dataset EGAD00001002885

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002891

• Genomic characterization of metastatic breast cancers

  This dataset contains all the .bam files used for the study.

  Dataset EGAD00001004772

• Genome and transcriptome sequence data from a metastatic rectal cancer patient

  Genome and transcriptome sequence data from a metastatic rectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004918

• Whole genome sequencing informs treatment decision of end-stage metastatic cutaneous angiosarcoma in a patient with Xeroderma Pigmentosum

  Whole genome sequencing (WGS) detects all mutations in a cancer. “Mutational signatures” are patterns of mutations that report the DNA damage and subsequent DNA repair processes that have occurred in cancers. We present a patient with Xeroderma Pigmentosum that developed metastatic angiosarcoma, unresponsive to all lines of sarcoma therapy. Primary tumour WGS revealed a hypermutated tumour, including clonal ultraviolet light-induced mutational patterns (Signature 7) and subclonal signatures of activating mutations of DNA Polymerase-epsilon (POLE)(Signature 10). These signatures are associated with response to immune-checkpoint blockade. Immunohistochemistry confirmed high PD-L1 expression in metastatic deposits. The patient was commenced on anti-PD-L1 therapy and has responded.

  Dataset EGAD00001004786

• Transcriptome profiling of prostate tissue samples from early onset prostate cancer patients and normal controls by RNA-seq

  The dataset contains RNA-seq data of 96 EOPC patients and 9 controls. For some patients multiple tissue samples were sequenced ("multi-area" samples). The RNA extraction and sequencing protocol was earlier described in Weischenfeldt et al, Cancer Cell, 2013.

  Dataset EGAD00001004791

• ETMR_Meth

  77 ETMR samples were profiled using methylation array. DNA from frozen tissue and formalin-fixed, paraffin-embedded (FFPE) materials were analyzed with the Illumina Infinium HumanMethylation450 (450k) and MethylationEPIC (EPIC) array according to manufacturer’s instructions and with a modified method that was previously described (Torchia et al. Cancer Cell. 2016; Triche et al. Nucleic Acids Res. 2013).

  Dataset EGAD00010001669

• RNA-Seq data from 34 CAF-S3 subset in human breast and ovarian cancers

  This dataset is related to publications Costa et al. Cancer Cell 2018 and Givel et al. Nat. Commun. 2018 which describe the identification of 4 Cancer Associated Fibroblasts (CAF) in breast and ovarian cancer. This dataset contains transcriptomic profiles obtained by RNA-Seq of 34 CAF-S3 samples from breast and ovarian Tumors.

  Dataset EGAD00001004810

• whole-genome sequencing of gastric cancer

  whole-genome sequencing of 168GCs identifies hot-spot tandem duplications

  Dataset EGAD00001004811

• 24 Chordoma samples (WES,WGS)

  Case series of the rare tumor entity chordoma. 9 cases sequenced with Whole Exome Sequencing (WES) and 2 cases sequenced with Whole Genome Sequencing (WGS) were recruited from the personalized oncology program NCT-MASTER/DKTK-MASTER at the German Cancer Research Center. One of the WES patients was re-sequenced at a later time point when he relapsed, this resequencing was done by WGS. Therefore there are 11 patients, one of which with two samples, all of which were sequenced with matched normal controls, amounting to a total number of 24 NGS samples.

  Dataset EGAD00001004825

• Whole genome sequencing of matched esophageal tumor-normal samples

  The dataset includes whole genome sequencing (WGS) data on ten matched esophageal tumor-normal pairs. WGS was performed by the cancer sequencing service of CG with an average read coverage of approximately 50-fold. Illumina HiSeq2000 instrument was used to perform the sequencing.

  Dataset EGAD00001004832

• Colorectal cancer methylation profiling

  4 AC samples, each with adenoma, carcinoma and normal colon tissue (12 samples in total) were analysed on the Infinium MethylationEPIC BeadChip for copy number alteration analyses.

  Dataset EGAD00010001691

• Korean Advanced Thyroid Cancer Dataset

  Massively-parallel DNA sequencing of 113 advanced thyroid cancers and Massively-parallel RNA sequencing of 25 advanced thyroid cancers

  Dataset EGAD00001004845

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004902

• Amplicon sequencing of adenoma to carcinoma paired samples from colon

  Colorectal cancer panel sequencing of 100 adenoma and carcinoma samples . Cancer Hot Spot panel sequencing of 7 samples from one poly.

  Dataset EGAD00001004848

• Genentech gallbladder cancer study - exome

  Genentech gallbladder cancer study - exome

  Dataset EGAD00001004853

• Genentech gallbladder cancer study - RNA-seq

  Genentech gallbladder cancer study - RNA-seq

  Dataset EGAD00001004854

• Genentech gallbladder cancer study - whole genome sequencing

  Genentech gallbladder cancer study - whole genome sequencing

  Dataset EGAD00001004855

• TONIC study RNASeq

  Transcriptome sequencing of 97 matched TNBC breast cancer metastasis samples obtained from 50 unique patients assayed at two timepoints: at baseline (directly after patient randomization), and post-induction treatment or control waiting period. The included raw transcriptome sequencing data (fastq-format) were generated using Illumina HiSeq2500 instruments.

  Dataset EGAD00001004858

• TONIC study Whole Exome Sequencing

  Paired-end whole exome sequencing of 50 TNBC breast cancer metastasis samples and matched normal samples obtained from 50 unique patients assayed at study baseline (directly after patient randomization). The included raw sequencing data (fastq-format) were generated using Illumina HiSeq2500 instruments.

  Dataset EGAD00001004857

• Preferential infiltration of unique Vγ9Jγ2‐Vδ2 T cells into glioblastoma multiforme

  Glioblastoma multiforme (GBM) is clinically highly aggressive as a result of evolutionary dynamics induced by cross-talk between cancer cells and a heterogeneous group of immune cells in tumor microenvironment. The brain harbors limited numbers of immune cells with few lymphocytes and macrophages; thus, innate‐like lymphocytes, such as γδ T cells, have important roles in antitumor immunity. Here, we characterized GBM‐infiltrating γδ T cells, which may have roles in regulating the GBM tumor microenvironment and cancer cell gene expression. V(D)J repertoires of tumor‐infiltrating and blood‐circulating γδ T cells from four patients were analyzed by next-generation sequencing-based T-cell receptor (TCR) sequencing in addition to mutation and immune profiles in four GBM cases. In all tumor tissues, abundant innate and effector/memory lymphocytes were detected, accompanied by large numbers of tumor‐associated macrophages and closely located tumor‐infiltrating γδ T cells, which appear to have anti-tumor activity. The immune-related gene expression analysis using the TCGA database showed that the signature gene expression extent of γδ T cells were more associated with those of cytotoxic T and Th1 cells and M1 macrophages than those of Th2 cells and M2 macrophages. Although the most abundant γδ T cells were Vγ9Vδ2 T cells in both tumor tissues and blood, the repertoire of intratumoral Vγ9Vδ2 T cells was distinct from that of peripheral blood Vγ9Vδ2 T cells and was dominated by Vγ9Jγ2 sequences, not by canonical Vγ9JγP sequences that are mostly commonly found in blood γδ T cells. Collectively, unique GBM‐specific TCR clonotypes were identified by comparing TCR repertoires of peripheral blood and intra‐tumoral γδ T cells. These findings will be helpful for the elucidation of tumor-specific antigens and development of anticancer immunotherapies using tumor-infiltrating γδ T cells.

  Dataset EGAD00001004862

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: kidney (2019-03-26)

  This dataset contains all the data available for this study on 2019-03-26.

  Dataset EGAD00001004867

• Genome and transcriptome sequence data from a squamous cell lung carcinoma patient

  Genome and transcriptome sequence data from a squamous cell lung carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004903

• Genetic alterations in benign breast biopsies of subsequent breast cancer patient

  This dataset consists of amplicon sequencing of fibrocystic breast tissues, subsequent cancer tissue and germline control of 17 patients. The target genes include all exons of 27 protein-coding genes and 2 non-coding genes, as well as mutation hotspots in three cancer genes, frequently mutated in breast cancer. Ion AmpliSeq libraries were generated and sequenced on the Ion S5 XL system.

  Dataset EGAD00001004874

• Proteogenomic Landscape of Curable Prostate Cancer

  Aligned RNA-seq sequences in this dataset are from the Proteogenomic Landscape of Curable Prostate Cancer study

  Dataset EGAD00001004875

• Targeted analysis of chondrosarcoma cancer genes (2019-04-01)

  Targeted analysis of chondrosarcoma cancer genes . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004877

• Evolution of the cancer epigenome in myeloproliferative neoplasms. (2019-04-01)

  Evolution of the cancer epigenome in myeloproliferative neoplasms. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004879

• Whole Exome PC9 and A375 (2019-04-03)

  Drug resistant population of PC9(human non-small cell lung cancer) or A375 (human melanoma) cell lines were used for this study. By exome sequencing, we will analyse mutations of cells in drug tolerent state and after drug holiday. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004891

• Genetic vulnerability of knockout cancer lines (2019-04-01)

  Genome-wide CRISPR/Cas9 library screen was performed in isogenic cell lines. Three biological replicates were used. Cells were harvested at initiation of screen and at specific time points following cell culture. Using this approach we aim to identify genes specifically important in cell survival in engineered cell lines. Please perform 72, instead of 36, PCR reactions as the screen performed at 200x coverage. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004881

• Exome sequencing of synchronous colorectal cancers

  The data consists of 47 exome-sequenced synchronous colorectal cancers from 23 patients. The exomes of corresponding normal samples were used to remove germline variants. All patients are Finnish (white Caucasian). All except one patient (sync_11 who belongs to a LS family) were assumed sporadic. The sequence data was produced with Illumina HiSeq 4000.

  Dataset EGAD00001004884

• Somatic mutations in twin breast cancers (2019-04-03)

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004890

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004917

• Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient

  Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004916

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004915

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004914

• Clonal haematopoiesis in patients with AAA (2019-04-03)

  Recent advances in genomics have demonstrated that clonal haemopoiesis driven by leukaemia associated somatic mutations is a relatively common phenomenon that increases in frequency with advancing age. Whilst individuals with clonal haemopoiesis have an increased risk of developing haematological malignancies, they also have an increased mortality from other causes. Additionally, certain mutations are almost exclusively seen in individuals aged 70 years or older, whilst others are seen in individuals with non-haematological cancers including breast and ovarian. Recently, clonal haemopoiesis was found to be associated with a significantly increased risk of atherosclerotic cardiovascular disease. This association is thought to be causative with clonally-derived macrophages showing elevated expression of several chemokine and cytokine genes that contribute to atherosclerosis. Another vascular pathology, abdominal aortic aneurysm (AAA), increases with age and shares risk factors with atherosclerosis (including smoking, male sex, high cholesterol). However, the impact of these risk factors and the overlap between AAA and atherosclerosis is poorly understood. To investigate a possible link between clonal haemopoiesis and AAA, we will study DNA samples from 300 patients with AAA and up to 200 controls for evidence of clonal haemopoiesis. This will be done using target DNA enrichment with biotinylated RNA baits followed by high throughput sequencing. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004895

• Predictor_RIO_TNBC (2019-04-03)

  In this study, samples fom a window study of the PARP inhibitor rucaparib in patients with primary triple negative or BRCA1/2 related breast cancer (RIO trial) will be investigated. Samples will undergo whole genome sequence and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004894

• Multi-Region WES of Metastatic Colorectal Cancer

  In order to reconstruct the evolutionary history of metastatic colorectal cancer, we performed whole-exome sequencing of 12 metastatic colorectal cancer patients for whom the primary tumor and matched distant metastases to the brain (n=10) and liver (n=2). For 8 of the 12 patients, multiple regions (n=3-7) of the primary tumor and distant metastases were sequenced.

  Dataset EGAD00001004896

• Genome and transcriptome sequence data from a locally advanced breast cancer patient

  Genome and transcriptome sequence data from a locally advanced breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004897

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004898

• Genome and transcriptome sequence data from a invasive ductal carcinoma of right breast patient

  Genome and transcriptome sequence data from a invasive ductal carcinoma of right breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004899

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004900

• Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient

  Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004901

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004910

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004923

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004922

• Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the breast patient

  Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004921

• Genome and transcriptome sequence data from a meningioma patient

  Genome and transcriptome sequence data from a meningioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004920

• Genome and transcriptome sequence data from a abdominal sarcoma patient

  Genome and transcriptome sequence data from a abdominal sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004919

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004913

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004912

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004911

• Genome and transcriptome sequence data from a metastatic serous ovarian cancer patient

  Genome and transcriptome sequence data from a metastatic serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004909

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004908

• Genome and transcriptome sequence data from a T-cell prolymphocytic leukemia patient

  Genome and transcriptome sequence data from a T-cell prolymphocytic leukemia patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004907

• Genome and transcriptome sequence data from a diffuse large B-cell lymphoma patient

  Genome and transcriptome sequence data from a diffuse large B-cell lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004906

• Genome and transcriptome sequence data from a metastatic adrenocortical carcinoma patient

  Genome and transcriptome sequence data from a metastatic adrenocortical carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004905

• Genome and transcriptome sequence data from a metastatic neuroendocrine tumor, lung primary patient

  Genome and transcriptome sequence data from a metastatic neuroendocrine tumor, lung primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004924

• Genome and transcriptome sequence data from a metastatic choroidal melanoma patient

  Genome and transcriptome sequence data from a metastatic choroidal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004925

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004926

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004927

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004928

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004929

• Genome and transcriptome sequence data from a metastatic ovarian cancer patient

  Genome and transcriptome sequence data from a metastatic ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004930

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004931

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004932

• Genome and transcriptome sequence data from a metastatic sarcomatoid carcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic sarcomatoid carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004933

• Genome and transcriptome sequence data from a squamous cell carcinoma of the alveolar ridge patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of the alveolar ridge patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004934

• Genome and transcriptome sequence data from a oligometastatic colorectal cancer patient

  Genome and transcriptome sequence data from a oligometastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004935

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004936

• Ovarian cancer sequencing dataset

  Sequencing data from patients with Ovarian cancer. Data utilised in the 'Enhanced detection of circulating tumor DNA by fragment size analysis' manuscript (Mouliere et al, 2018)

  Dataset EGAD00001004939

• Field effect of healthy and diseased livers (2019-04-08)

  Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences). . This dataset contains all the data available for this study on 2019-04-08.

  Dataset EGAD00001004941

• Lung cancer organoids addition

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004943

• Epithelial, fibroblast, myeloid, T cell, primary prostate cancer

  The collection and use of tissue for this study had Melbourne Health institutional review board approval and patients provided written informed consent (Melbourne Health Local Project Number: 2016.087). Following the prostatectomy of 13 patients, ranging from 52 to 78 years of age and from CAPRA-S risk score of 0 (attributed to benign tissue samples, harvested from a site far from a low grade, low volume cancer) to 7 (Supplementary file 2), a four millimeter tissue core was collected from the prostate tumour site, conditional to histopathological verification66,67. If not otherwise specified, all procedures were carried out at 4 °C. Tissue blocks were washed in Phosphate-buffered saline (PBS) solution for 2 minutes and minced for 2 minutes with a scalpel. Homogenised tissue was added to a solution (total volume of 7 ml) composed by of 1 mg/ml collagenase IV (Worthington Biochemical Corp, USA), 0.02 mg/ml DNase 1 (New England Biolabs, USA), 0.2 mg/ml dispase (Merck, USA). The tissue homogenised was serially digested at 37 °C at 180 rpm, through three steps of 5, 10 and 10 minutes of duration, with the final 3 minutes dedicated to sedimentation at 0 rpm. After each digestion step, the supernatant was aspirated and filtered through a 70 μm strainer into a pre-chilled tube, diluting the solution with 15 ml of 2% bovine serum PBS to quench the enzymatic reaction. The resulting cumulative solution was then centrifuged at 1500 rpm for five minutes, with the supernatant collected and the cell pellet resuspended into 1 ml 2% PBS-serum prior to labelling (Fig. S1).

  Dataset EGAD00001004948